Strengthening marriages is important to the well-being of individuals, families and communities. The transition to parenthood brings with it particular risks and opportunities for marriage relationships, yet no interventions have been successful in accessing a large number of couples during this critical time prepare and strengthen them for the challenges of becoming parents. The healthcare system has an established education infrastructure (childbirth education) that interacts with a significant number of couples during the transition to parenthood and has become increasingly open to incorporating relationship strengthening efforts into existing programs. The Marriage Moments program was designed to access couples through this system. This new approach to marriage education employs a program design unique in three ways: the context of childbirth education, a low-intensity content based on a model of marital virtues, and a simple, self-administered format of materials that gives the program great flexibility and transportability that can be implemented in a variety of existing systems. Initial formative program evaluation data show that the program is well received by participating couples. Marriage Moments is currently being pilot tested to evaluate its effectiveness in strengthening marriage through the transition, but it is expected the program will be disseminated widely and reach numerous couples as they transition to parenthood.

<p>Two-phase modeling and simulation capabilities are strongly dependent on the accuracy of flow regime identification methods. Flow regimes have traditionally been determined through visual observation, resulting in subjective classifications that are susceptible to inconsistencies and disagreements between researchers. Since the majority of two-phase flow studies have been concentrated around vertical and horizontal pipe orientations, flow patterns in inclined pipes are not well-understood. Moreover, they may not be adequately described by conventional flow regimes which were conceptualized for vertical and horizontal flows. Recent work has explored applying machine learning methods to vertical and horizontal flow regime identification to help remedy the subjectivity of classification. Such methods have not, however, been successfully applied to inclined flow orientations. In this study, two novel unsupervised machine learning methods are proposed: a modular configuration of multiple machine learning algorithms that is adaptable to different pipe orientations, and a second universal approach consisting of several layered algorithms which is capable of performing flow regime classification for data spanning multiple orientations. To support this endeavor, an experimental database is established using a dual-ring impedance meter. The signals obtained by the impedance meter are capable of conveying distinct features of the various flow patterns observed in vertical, horizontal, and inclined pipes. Inputs to the unsupervised learning algorithms consist of statistical measures computed from these signals. A novel conceptualization for flow pattern classification is developed, which maps three statistical parameters from the data to red, green, and blue primary color intensities. By combining the three components, a flow pattern map can be developed wherein similar colors are produced by flow conditions with like statistics, transforming the way flow regimes are represented on a flow regime map. The resulting dynamic RGB flow pattern map provides a physical representation of gradual changes in flow patterns as they transition from one regime to another. By replacing the static transition boundaries with physically informed, dynamic gradients between flow patterns, transitional flow patterns may be described with far greater accuracy. This study demonstrates the effectiveness of the proposed method in generating objective flow regime maps, providing a basis for further research on the characterization of two-phase flow patterns in inclined pipes. The three proposed methods are compared and evaluated against flow regime maps found in literature.</p>

<p>Nuclear engineering hosts diverse domains including, but not limited to, power plant automation, human-machine interfacing, detection and identification of special nuclear materials, modeling of reactor kinetics and dynamics that most frequently are described by systems of differential equations (DEs), either ordinary (ODEs) or partial ones (PDEs). In this work we study multiple problems related to safety and Special Nuclear Material detection, and numerical solutions for partial differential equations using neural networks. More specifically, this work is divided in six chapters. Chapter 1 is the introduction, in Chapter</p> <p>2 we discuss the development of a gamma-ray radionuclide library for the characterization</p> <p>of gamma-spectra. In Chapter 3, we present a new approach, the ”Variance Counterbalancing”, for stochastic</p> <p>large-scale learning. In Chapter 4, we introduce a systematic approach for constructing proper trial solutions to partial differential equations (PDEs) of up to second order, using neural forms that satisfy prescribed initial, boundary and interface conditions. Chapter 5 is about an alternative, less imposing development of neural-form trial solutions for PDEs, inside rectangular and non-rectangular convex boundaries. Chapter 6 presents an ensemble method that avoids the multicollinearity issue and provides</p> <p>enhanced generalization performance that could be suitable for handling ”few-shots”- problems frequently appearing in nuclear engineering.</p>

<p>  </p> <p>The study of two-phase flow in different orientations can allow for greater understanding of the fundamentals of two-phase flow dynamics. While a large amount of work has been performed for vertical flows and recent work has been done for horizontal flows, limited research has been done studying inclined upward two-phase flows between those two orientations. Studying two-phase flows at various inclinations is important for developing physical models and simulations of two-phase flow systems and understanding the changes between what is observed for symmetric vertical flows and asymmetric horizontal flows. The present work seeks to systematically characterize the effects of inclination on adiabatic concurrent air-water two-phase flows in straight pipes. An experimental database is established for local and global two-phase flow parameters in a novel inclinable 25.4 mm inner diameter test facility using four-sensor conductivity probes, high speed video capabilities, a ring-type impedance meter, a pressure transducer, and a gamma densitometer. Rotatable measurement ports are employed to allow for local conductivity probe measurements across the flow profile to capture asymmetric parameter distributions during experiments without stopping the flow. Some of the major effects of inclination are investigated, including the effects on flow regime transition, bubble distribution, frictional pressure loss, and relative motion between the two phases. Flow visualization and machine-learning methods are employed to identify the transitions between flow regimes for inclined orientations, and these transitions are compared against existing theoretical flow regime transition criteria proposed in literature. The theoretical transitions in literature agree well with both methods for vertical flow, but additional work is necessary for angles between 0 degrees and 60 degrees. The effect of inclination on two-phase frictional pressure drop is explored, and a novel adaption of the Lockhart-Martinelli pressure drop correlation is proposed, which is able to predict the pressure drop for the conditions investigated with an absolute percent difference of 2.6%. To explore the relationships between orientation, void fraction, and relative motion, one-dimensional drift flux analyses are performed for the data at each angle investigated. It is observed that the relative velocity between phases decreases as the angle is reduced, with a relative velocity near zero at some intermediate angles and a negative relative velocity for near-horizontal orientations.  Existing modeling capabilities that have been developed for vertical and horizontal flows are evaluated based on the local two-phase parameters collected at multiple orientations. The performance of the one-dimensional interfacial area transport equation for vertical and horizontal flows is tested against experimental data and a novel model for horizontal and inclined-upward bubbly flows is proposed. Finally, an evaluation of existing momentum transfer relations is performed for the two-fluid model using three-dimensional computational fluid dynamics tools for horizontal and inclined. The prediction of the void fraction distribution and gas velocity profiles are compared against experimental data, and improvements to the lift force model are identified based on changes in the relative velocity between phases. </p>

<p> Wire-wrapped rod bundles are often used in nuclear reactors operating in a fast neutron spectrum, as designers seek to minimize neutron scattering by packing the fuel pins into a hexagonal lattice. Bundles with many rods have extensively been studied as representative of large fuel assemblies, however far fewer experiments have investigated bundles with 7 rods (7-pin bundles). The large difference in subchannel number between these bundles leads to 7-pin bundles having different pressure drop characteristics. The Versatile Test Reactor (VTR) sodium cartridge loop proposes to use a 7-pin bundle as its experimental core region, highlighting the need for additional data and models. The current work seeks to establish a better understanding of the pressure drop in 7-pin wire-wrapped rod bundles through scaled experiments and a novel pressure drop model. A scaling analysis is first performed to demonstrate the applicability of water experiments to the VTR sodium cartridge loop, before an experimental test facility is designed and constructed. Experiments are then performed at a range of Reynolds numbers to determine the pressure drop. Current models are able to predict the data well, but are complex and can be difficult to use. A comparatively simpler model is developed, based on exact laminar solutions of a simplified rod bundle, which also offers a theoretical lower bound for the pressure drop in wire-wrapped bundles. The proposed model compares well with the existing experimental database, able to predict bundle friction factor with an average absolute percent difference of 10.8%. This accuracy is also similar to existing correlations, while relying on fewer empirical coefficients. The theoretical lower bound is also used to identify several datasets in literature that may feature data that is systemically lower than the true pressure drop, which agrees with previous observations in literature. </p>

[ES] La seguridad alimentaria es una prioridad para la población y en la actualidad cobra mayor importancia por ciertas tendencias alimentarias como el consumo de alimentos crudos y la distribución generalizada de alimentos orgánicos, que pueden ser la causa de enfermedades transmitidas por alimentos. Para garantizar la seguridad alimentaria, la detección de estos microorganismos debe realizarse de manera rápida y eficiente. Par eso, el método de cultivo microbiológico se considera el oficial para la detección de estos patógenos. Sin embargo, adolece de importantes inconvenientes, ya que no solo requiere mucho tiempo, sino que también es laborioso y consume muchos recursos. Además, puede ser limitado con respecto a la detección de bacterias fisiológicamente alteradas y/o estresadas durante el almacenamiento y la conservación. En este trabajo se ha desarrollado un protocolo sencillo y rápido para la detección simultánea de E. coli, L. monocytogenes, S. aureus y S. enterica en alimentos, mediante la combinación de una etapa de co-cultivo en medio líquido y la detección por PCR múltiple. Se ha evaluado la eficiencia de varios medios de enriquecimiento y se seleccionó el agua de peptona tamponada como el medio óptimo para el co-cultivo de las cuatro bacterias diana. También se optimizaron las condiciones de PCR múltiple y se aplicaron tanto a co-cultivos como a muestras de alimentos inoculados artificialmente, lechuga orgánica y carne picada. Después de la optimización, la PCR múltiple desarrollada fue capaz de detectar las cuatro bacterias simultáneamente, hasta con una inoculación inicial de 10^0 UFC/mL. En presencia de ambas matrices alimentarias inoculadas, tras la etapa de co-cultivo, la PCR múltiple pudo detectar simultáneamente las 3 bacterias E. coli, S. enterica y L. monocytogenes, mientras que S. aureus se ha detectado por PCR simplex, a partir del mismo extracto de ADN del co-cultivo. Los resultados obtenidos permiten concluir que el uso de un paso de co-cultivo en Agua peptona tamponada, antes de la detección por PCR simple y múltiple, puede facilitar la detección simultánea de las cuatro bacterias potencialmente presentes en las matrices alimentarias. La presencia o ausencia de la bacteria diana en los alimentos se confirma en unas 30 horas, lo que reduce el tiempo requerido para la detección en comparación con el tiempo mínimo de 7 días por método cultural. Asimismo, permite reducir el número de medios de cultivo y reactivos, para el aislamiento e identificación de bacterias que no son detectadas por PCR y que no están presentes en las matrices alimentarias, lo que supone un importante ahorro económico. / [CA] La seguretat alimentària sempre és una prioritat per a la població i en l' actualitat cobra major importància per certes tendències alimentàries, com el consum d' aliments crus i la distribució generalitzada d' aliments orgànics, que poden ser la causa de malalties transmeses per aliments. Per garantir la seguretat alimentària, la detecció d' aquests microorganismes s' ha de realitzar de manera ràpida i eficient. Per a això, el mètode de cultiu microbiològic es considera l' oficial per a la detecció d' aquests patògens. Però, hi ha importants inconvenients, ja que no només requereix més temps, sinó que també és laboriós i consumeix molts recursos. A més, pot ser limitat pel que fa a la detecció de bacteris fisiològicament alterats i/o estressats durant l'emmagatzematge i la conservació. En aquest treball s'ha desenvolupat un protocol senzill i ràpid per a la detecció simultània d' E. coli, L. monocytogenes, S. aureus i S. enterica en aliments, mitjançant la combinació d' una etapa de co-cultiu en medi líquid i la detecció per PCR múltiple. S'ha avaluat l'eficiència de diversos mitjans d'enriquiment i s'ha seleccionat l'aigua de peptona tamponada com el medi òptim per al co-cultiu dels quatre bacteris diana. També es van optimitzar les condicions de PCR múltiple i es van aplicar tant a co-cultius com a mostres d'aliments inoculats artificialment, enciam orgànic i carn picada. Després de l'optimització, la PCR múltiple desenvolupada va ser capaç de detectar els quatre bacteris simultàniament, fins a una inoculació inicial de 10^0 UFC/mL. En presència d' ambdues matrius alimentàries inoculades, després l' etapa de co-cultiu, la PCR múltiple va poder detectar simultàniament els 3 bacteris: E. coli, S. enterica i L. monocytogenes, mentre que S. aureus s' ha detectat per PCR simple, a partir del mateix extracte d' ADN del co-cultiu. Els resultats obtinguts permeten concloure que l' ús d' un pas de co-cultiu en Aigua de peptona tamponada, abans de la detecció per PCR simple i múltiple, pot facilitar la detecció simultània dels quatre bacteris potencialment presents en les matrius alimentàries. La presència o absència del bacteri diana en els aliments es confirma en unes 30 hores, la qual cosa redueix el temps requerit per a la detecció en comparació amb el temps mínim de 7 dies per mètode cultural. Així mateix, permet reduir el nombre de mitjans de cultiu i reactius, per a l' aïllament i identificació de bacteris que no són detectats per PCR i que no estan presents en les matrius alimentàries, la qual cosa suposa un important estalvi econòmic. / [EN] Food safety is a priority for the population and is nowadays more important than ever due to certain dietary trends such as the consumption of raw foods and the widespread distribution of organic foods, which may be the cause of foodborne diseases. To ensure food safety, the detection of these microorganisms must be done quickly and efficiently. Although, the microbiological culture method is considered to be the official method for the detection of these food-borne pathogens, it suffers from significant drawbacks, such as time-consuming, laborious and expensive, in addition it may be limited regarding the detection of physiologically altered and/or stressed bacteria, during storage and preservation. In this work has been developed a simple and rapid protocol for the simultaneous detection of E. coli, L. monocytogenes, S. aureus and S. enterica in food, by combining a liquid co-culture step and detection by multiplex PCR. The efficiency of several enrichment media was evaluated and buffered peptone water was chosen as the optimal medium for the co-culture of the four target bacteria. Then, optimized multiplex PCR conditions were applied to both the co-cultures and the samples of artificially inoculated foods, organic lettuce and ground meat. After optimization, the developed multiplex PCR was able to simultaneously detect the four bacteria, up to an initial inoculation of 10^0 CFU/mL. In the presence of the two inoculated food matrices, after a co-culture step, the multiplex PCR could simultaneously detect the 3 bacteria: E. coli, S. enterica and L. monocytogenes, whereas, S. aureus has been detected by simplex PCR, from the same co-culture DNA template. The results obtained allow conclusion that the use of a co-culture step in Buffered Peptone Water, before detection by simplex and multiplex PCR, can facilitate the simultaneous detection of the four bacteria potentially present in the food matrices. The presence or the absence of the target bacteria in food is confirmed in approximately 30 hours, which reduce the time required for the detection compared to the minimum time of 7 days by cultural method. Also, it allows to reduce the number of culture media and reagents, for the isolation and identification of bacteria that are not detected by PCR and which are not initially present in the food matrices, which represents a significant economic savings. / Boukharouba, A. (2022). Isolation and Identification of Foodborne Pathogens of Special Interest in Food Safety [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/182828

<p>Modern reactors promise enhanced capabilities not previously possible including integration with the smart grid, remote monitoring, reduced operation and maintenance costs, and more efficient operation. . Modern reactors are designed for installation to remote areas and integration to the electric smart grid, which would require the need for secure undisturbed remote control and the implementation of two-way communications and advanced digital technologies. However, two-way communications between the reactor facility, the enterprise network and the grid would require continuous operation data transmission. This would necessitate a deep understanding of cybersecurity and the development of a robust cybersecurity management plan in all reactor communication networks. Currently, there is a limited number of testbeds, mostly virtual, to perform cybersecurity research and investigate and demonstrate cybersecurity implementations in a nuclear environment. To fill this gap, the goal of this thesis is the development of a real-time cyber-physical testbed with real operational and information technology data to allow for cybersecurity research in a representative nuclear environment. In this thesis, a prototypic cyber-physical testbed was designed, built, tested, and installed in PUR-1. The cyber-physical testbed consists of an Auxiliary Moderator Displacement Rod (AMDR) that experimentally simulates a regulating rod, several sensors, and digital controllers mirroring Purdue University Reactor One (PUR-1) operation. The cyber-physical testbed is monitored and controlled remotely from the Remote Monitoring and Simulation Station (RMSS), located in another building with no line of sight to the reactor room. The design, construction and testing of the cyber-physical testbed are presented along with its capabilities and limitations. The cyber-physical testbed network architecture enables the performance of simulated cyberattacks including false data injection and denial of service. Utilizing the RMSS setup, collected information from the cyber-physical testbed is compared with real-time operational PUR-1 data in order to evaluate system response under simulated cyber events. Furthermore, a physics-based model is developed and benchmarked to simulate physical phenomena in PUR-1 reactor pool and provide information about reactor parameters that cannot be collected from reactor instrumentation system.</p>

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<p dir="ltr">For additive manufacturing to be a viable method to build metal parts for industries such as nuclear, the manufactured parts must be of higher quality and have lower variation in said quality than what can be achieved today. This high variation in quality bars the techniques from being used in high safety tolerance fields, such as nuclear. If this obstacle could be overcome, the benefits of additive manufacturing would be in lower cost for complex parts, as well as the ability to design and test parts in a very short timeframe, as only the CAD model needs to be created to manufacture the part. In this study, work to achieve this lower variation of quality was approached in two ways. The first was in the development of surrogate models, utilizing machine learning, to predict the end quality of additively manufactured parts. This was done by using experimental data for the mechanical properties of built parts as outputs to be predicted, and in-situ signals captured during the manufacturing process as inputs to the model. To capture the in-situ signals, cameras were used for thermal and optical imaging, leveraging the natural layer-by-layer manufacturing method used in AM techniques. The final models were created using support vector machine and gaussian process regression machine learning algorithms, giving high correlations between the insitu signals and mechanical properties of relative density, elongation to fracture, uniform elongation, and the work hardening exponent. The second approach to this study was in the development of a reduced order model for a computer simulation of an AM build. For project, a ROM was built inside the MOOSE framework, and was developed for an AM model designed by the MOOSE team, using proper orthogonal decomposition to project the problem onto a lower dimensional subspace, using POD to design the reduced basis subspace. The ROM was able to achieve a reduction to 1% the original dimensionality of the problem, while only allowing 2-5% relative error associated with the projection.</p>